The Use of Non-Linear Regression Methods for Analyzing Sensitivity and Quantal Response Data

Biometrics ◽  
1967 ◽  
Vol 23 (3) ◽  
pp. 563 ◽  
Author(s):  
R. H. Moore ◽  
R. K. Zeigler
2018 ◽  
Vol 136 ◽  
pp. 199-206
Author(s):  
Donald Raoul Tchuifon Tchuifon ◽  
George Nche Ndifor-Angwafor ◽  
Aurelien Bopda ◽  
Solomon Gabche Anagho

1990 ◽  
Vol 265 (3) ◽  
pp. 647-653 ◽  
Author(s):  
S E Szedlacsek ◽  
V Ostafe ◽  
R G Duggleby ◽  
M Serban ◽  
M O Vlad

The rate equation for a tight-binding inhibitor of an enzyme-catalysed first-order reversible reaction was used to derive two integrated equations. One of them covers the situations in which competitive, uncompetitive or non-competitive inhibition occurs and the other refers to the special non-competitive case where the two inhibition constants are equal. For these equations, graphical and non-linear regression methods are proposed for distinguishing between types of inhibition and for calculating inhibition constants from progress-curve data. The application of the non-linear regression to the analysis of stimulated progress curves in the presence of a tight-binding inhibitor is also presented. The results obtained are valid for any type of ‘dead-end’-complex-forming inhibitor and can be used to characterize an unknown inhibitor on the basis of progress curves.


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